Your research sources are contradicting each other. How do you validate your findings?
When your research sources contradict each other, it's essential to determine which information is reliable. Here's how to validate your findings:
What strategies have you found helpful for validating conflicting research?
Your research sources are contradicting each other. How do you validate your findings?
When your research sources contradict each other, it's essential to determine which information is reliable. Here's how to validate your findings:
What strategies have you found helpful for validating conflicting research?
-
This question appears to be premised around social research or qualitative-focused research. If that is the case, then (in addition to cross-referencing sources), one could dig into literature on cases on that subject under investigation(if the subject is well published). However, for general interest... For quantitative data, it may be necessary to engage in checking the actual source of contradictions. A starting point would be to so multiple checks by doing content, criterion-related, construct and face validity. For qualitative research, it could help to check credibility, transferability, dependability, and confirmability. For mixed research methodology, a combination would work depending on what the objectives are.
-
It's okay if that is the case especially if it is a social research as all people perceive the same situations/ scenario in different manner. I would suggest to embrace the varied perspective and focus it in your findings.
-
When research sources contradict I usually check the source's credibility, I look at who wrote the information. Trusted sources like reputable news outlets, academic journals, or recognized experts in the field are more reliable. I also compare multiple sources, I compare information from several places to see if there's a common agreement. I check the publication date as well, newer information are likely to be more accurate.
-
Actually, this can be a good thing. First, it means you dug the data well. Thus it may be time to design secondary tool to collect additional information for triangulation (using multiple sources or tools to crosscheck and validate) of information and sources. For instance, one can choose to conduct an observation (if there is significant unrestricted access, and it is possible) to validate information provided by different sources. This can help validate data in many ways.
-
Personally, I consider that a way of digging deep. Consult literature, reliable publications known for its credible sources and if possible other experts in the field. I then sit and anlayse based on all the infomation acquired.
-
My research in past years have contradicting findings. Generally in social sciences, many researcher dont call for contradicting theories for many reasons, but this is the beauty of social science research. We can have contradicting findings, validate them, but only if it is credible, unbiased, and taken out from original sources.
-
Here’s a detailed approach based on the type of research (survey, experimental, or theoretical): For Survey-Based Research Fresh data collection/Conditional Validation/Gap analysis/ Transparency (declaration) For Experimental Research Inter,Intra variability in context to place, time and sample groups/ Protocols and SOPs/Repeatability and Reproduciblity/Data Triangulation For Theoretical, Logical and Philosophical Research Proof Theory/ Perspective Differences / Critical Appraisals/ Explanatory models General Practices For Validation and Re-Standardisation Meta-analysis / Re-Standardisation/full declaration Contradictions then become an opportunity for deeper understanding rather than a limitation.
-
Rarely in applied sciences to find contradictory results for the same research concept if the study was repeated precisely. However, in case you have done a research protocol in one country, and same protocol was applied in other country, you might find some contradictory results due to variations in environment, personnel, and other hidden factors.
-
I feel like this is a flawed question. If my secondary research sources offer contradictory findings, well, it's interesting to me, isn't it? I think this question shows a bias toward an assumption that we are all driven by positivist assumptions & that contradictory data would be distressing. Because my area generally is driven by non-positivist assumptions (i.e., rejecting the assumption of generalisability & predictive power), and uses case study analysis, relatively small qualitative study data, the focus is on gaining a rich, targeted insight into specific cases. So it's fine if they show me different outcomes. I'm not trying to generalise anything, nor am I trying to work to a hypothesis that I would need to reject or accept.
Rate this article
More relevant reading
-
Scientific WritingHow do you prioritize and scope future work based on your research findings?
-
Research ManagementHow can you write a compelling conclusion to a scientific paper?
-
ResearchWhat do you do if you need to assess the credibility of research findings using logical reasoning?
-
ResearchHow do you identify and fill the gaps in the existing literature?